An ACO Algorithm for Effective Cluster Head Selection

This paper presents an effective algorithm for selecting cluster heads in mobile ad hoc networks using ant colony optimization. A cluster in an ad hoc network consists of a cluster head and cluster members which are at one hop away from the cluster head. The cluster head allocates the resources to its cluster members. Clustering in MANET is done to reduce the communication overhead and thereby increase the network performance. A MANET can have many clusters in it. This paper presents an algorithm which is a combination of the four main clustering schemes- the ID based clustering, connectivity based, probability based and the weighted approach. An Ant colony optimization based approach is used to minimize the number of clusters in MANET. This can also be considered as a minimum dominating set problem in graph theory. The algorithm considers various parameters like the number of nodes, the transmission range etc. Experimental results show that the proposed algorithm is an effective methodology for finding out the minimum number of cluster heads.Comment: 7 pages, 5 figures, International Journal of Advances in Information Technology (JAIT); ISSN: 1798-2340; Academy Publishers, Finlan

Simultaneous Coherent Structure Coloring facilitates interpretable clustering of scientific data by amplifying dissimilarity

The clustering of data into physically meaningful subsets often requires assumptions regarding the number, size, or shape of the subgroups. Here, we present a new method, simultaneous coherent structure coloring (sCSC), which accomplishes the task of unsupervised clustering without a priori guidance regarding the underlying structure of the data. sCSC performs a sequence of binary splittings on the dataset such that the most dissimilar data points are required to be in separate clusters. To achieve this, we obtain a set of orthogonal coordinates along which dissimilarity in the dataset is maximized from a generalized eigenvalue problem based on the pairwise dissimilarity between the data points to be clustered. This sequence of bifurcations produces a binary tree representation of the system, from which the number of clusters in the data and their interrelationships naturally emerge. To illustrate the effectiveness of the method in the absence of a priori assumptions, we apply it to three exemplary problems in fluid dynamics. Then, we illustrate its capacity for interpretability using a high-dimensional protein folding simulation dataset. While we restrict our examples to dynamical physical systems in this work, we anticipate straightforward translation to other fields where existing analysis tools require ad hoc assumptions on the data structure, lack the interpretability of the present method, or in which the underlying processes are less accessible, such as genomics and neuroscience

Assessing the conservation value of waterbodies: the example of the Loire floodplain (France)

In recent decades, two of the main management tools used to stem biodiversity erosion have been biodiversity monitoring and the conservation of natural areas. However, socio-economic pressure means that it is not usually possible to preserve the entire landscape, and so the rational prioritisation of sites has become a crucial issue. In this context, and because floodplains are one of the most threatened ecosystems, we propose a statistical strategy for evaluating conservation value, and used it to prioritise 46 waterbodies in the Loire floodplain (France). We began by determining a synthetic conservation index of fish communities (Q) for each waterbody. This synthetic index includes a conservation status index, an origin index, a rarity index and a richness index. We divided the waterbodies into 6 clusters with distinct structures of the basic indices. One of these clusters, with high Q median value, indicated that 4 waterbodies are important for fish biodiversity conservation. Conversely, two clusters with low Q median values included 11 waterbodies where restoration is called for. The results picked out high connectivity levels and low abundance of aquatic vegetation as the two main environmental characteristics of waterbodies with high conservation value. In addition, assessing the biodiversity and conservation value of territories using our multi-index approach plus an a posteriori hierarchical classification methodology reveals two major interests: (i) a possible geographical extension and (ii) a multi-taxa adaptation

An energy-efficient clustering protocol using fuzzy logic and network segmentation for heterogeneous WSN

Wireless sensor networks have become an emerging research area due to their importance in the present industrial application. The enlargement of network lifetime is the major limitation in WSN. Several routing protocols study the extension of lifespan in WSN. Routing protocols significantly influence on the global of energy consumption for sensors in WSN. It is essential to correct the energy efficiency performance of routing protocol in order to improve the lifetime. The protocols based on clustering are the most routing protocols in WSN to reduce energy consumption. The protocols dedicate to WSN have demonstrated their limitation in expanding the lifetime of the network. In this paper, we present Hybrid SEP protocol : Multi-zonal Fuzzy logic heterogeneous Clustering based on Stable Election Protocol (FMZ-SEP). The FMZ-SEP characterizes by four parameters: WSN segmentation (splitting the WSN into the triangle zones ), the Subtractive Clustering Method to determine a correct number of clusters, the FCM and the SEP protocol. The FMZ-SEP prolong the stability period and extend the lifetime. The simulation results point out that the stability period of FMZ-SEP. FMZ-SEP protocol outperforms of MZ-SEP, FSEP and SEP protocol by improving the network lifetime and the stability period

Enhancement of Performance Metrics of Heterogeneous Wireless Camera Sensor Network with Functionalization of Extensive Zonal Stable Election Protocol using Threshold Amplification and Residual Energy

We report a new improved energy competent and optimized data packet flow protocol with Hierarchical Clustering utilized in Wireless camera Sensor Network.The existing Extensive Zonal Stable Election Protocol has been modified along with the threshold parameters amplification and residual energy. It incorporates dynamic hybrid method with finite number of Member Sensor nodes (MSN) in proximity with the base station share their data directly , while the rest of the farther nodes form a cluster for data transference using Cluster Head. The performance metrics accompanied by heterogeneity, longer network survival and better throughput have been improved. The network field was divided into 4 zones with a gateway for defined region 2, 3, and 4. The criterion for zone division remained on the energy status (residual) of the MSNs and distance from the BS and the formulated field characteristics in the simulation were kept unknown. The obtained results demonstrate that our proposed modified version of EZSE protocol considerably performs better than existing EZ-SEP, Z-SEP, SEP, LEACH, Mod-Leach protocols during entire stability timeframe. The notable achievement is also reported in throughput as the same is enhanced more than  by ~ 39%, 43%, 49% ,56%, 53% while total packets communicated with base station has been increased more than by ~ 127%, 131%, 147%, 151%, 148% stability of the network is also improved more than by ~ 37%, 42%, 45%, 49%, 51% with the corresponding increase in the heterogeneity of networks

Extending TRANSIMS Technology to an Integrated Multilevel Representation

The TRANSIMS system developed at Los Alamos in the USA over the past decade is a world leader in providing an integrated land-use transportation dynamical model for large areas with a million or more inhabitants. TRANSIMS uses standard survey data to create synthetic micropopulations, including family structure, to simulate trip making and emergent traffic dynamics. We propose to extend TRANSIMS by adapting it to a new multi-level representation, allowing dynamics to be algebraically integrated at the micro-, meso- and macro-levels. The new representation builds a lattice hierarchy in a way that integrates non-partitional hierarchies of links and routes based on the usual hierarchy of geographical zones, e.g. neighbourhoods, districts, cities, counties and countries. Applying the representation to a big city starts by defining sets of zones at different levels. At the first level, N, is the street. This can be subdivided to building plots at level N-1, buildings at level N-2, and even rooms at level N-3. At level N+1 are the neighbourhoods, at level N+2 is the set of district zones (each of them containing the different neighbourhoods in the previous level), and at the top level N+3 (in this case), is just one zone, the city itself. If a larger study area is to be considered, we would have a whole set of N+3 zones defining N+4-level areas, and so on, extending to the level of counties, countries or even continents. This paper will explain the fundamentals of TRANSIMS technology and compare it to other systems. We will show how TRANSIMS and the new multi-level representation can be brought together to give new insights into the macro-dynamics of very large road systems such as London, England and even the whole of Europe

Multicasting Model for Efficient Data Transmission in VANET

VANETs (Vehicle Ad hoc Networks) are networks made up of a number of vehicular nodes that are free to enter and leave the network. The Location Aided Routing (LAR) protocol is the one that is most frequently utilized among them. Here, the route request packets are flooded across many pathways to the source node using the broadcasting strategy. The vehicles that have a direct path to the destination send the route reply packets back to the source. The least number of hops and the sequence number are used to determine the route from source to destination. This research study has used the multicasting approach to construct a path from the source node to the destination node. Within this multicasting strategy, the root nodes from the network are selected for data routing. The path between the source and the destination is chosen using a root node. The suggested approach is put into practice using the NS2, and some parametric values are computed to produce analytical findings

An Empirical Analysis of cluster-based routing protocols in wireless sensor network

Wireless Sensor Networks (WSNs) are utilized for condition monitoring, developing the board, following animals or goods, social protection, transportation, and house frameworks. WSNs are revolutionizing research. A WSN includes a large number of sensor nodes, or bits, in the application. Bits outfitted with the application\u27s sensors acquire nature data and send it to at least one sink center (in like manner called base stations). This article simulates energy-efficient network initialization strategies using simulation models. First, an overview of network initiation and exploration procedures in wireless ad-hoc networks is provided. The clustering-based routing strategy was selected since it\u27s best for ad-hoc sensor networks. The clustering-based routing techniques used for this study are described below. LEACH, SEP, and Z-SEP are used. MATLAB was used to implement and simulate all routing protocols. All protocols were simulated with various parameters like Number of CHs, Number of Alive Nodes, Number of Dead Nodes, Number of packets to BS, and circumstances to show their functioning and to determine their behavior in different sensor networks